SICAR como ferramenta de análise e tendência do desmatamento na região norte do Brasil

Abstract

The present work consists of the combination of remote sensing tools that allows the detection of deforestation with the explanatory component that SICAR offers, and other bases of land tenure, which can identify areas of significant carbon loss resulting from deforestation. Thus, this study aims to analyze and demonstrate the trend of deforestation in the Amazon rainforest of northern Brazil in a historical series from 2008 to 2016, with specific objectives of understanding the evolution of deforestation after the institution of areas of consolidated use until the year 2016, in the states of Pará and Amazonas; Analyze the patterns of deforested areas according to the land tenure structure of the states, regarding the different types of properties (public, settlements, private and protected) and property size; Quantify lost biomass and carbon emissions from deforestation in the historical series from 2008 to 2016 in the states under study. In the methodology, "Remote Sensing" or GIS tools and tables were used to process the data provided by LEMAF / UFLA, such as the Sicar database and the Monitoring project of the states under study. Much of the deforestation that occurred in the surveyed states (PA and AM) in northern Brazil between 2008-2016 was in the state of Pará, equivalent to 69% of the total; Private properties were largely responsible for deforestation, with 25,876 km² deforested; Smaller properties tend to deforest larger areas in percentage terms and were responsible for the highest rate of deforestation, equivalent to 19% of the total; in Amazonas, large properties were the main agents of deforestation, while in Pará, they were the smallest properties; The deforestations that occurred between 2008-2016 were responsible for the emission of 58.98 Tg of CO2 Equivalent. In which private properties were largely responsible for this emission, specifically large and small properties, with 5.55 Tg and 5.83 Tg of CO2 Equivalent. The largest carbon stocks are concentrated in protected areas. Finally, the survey concluded that the increase in spatial resolution improves the ability to monitor previously undetected deforested areas and the results show that remote sensing data together with data from land tenure are promising tools to understand the dynamics of deforestation, but still there are many improvements that must be made, mainly land regularization, so that there is no overlap between properties, and can identify those responsible for deforestation.